Summary

Proceedings of the 2012 International Symposium on Nonlinear Theory and its Applications

2012

Session Number:A1L-B

Session:

Number:33

Nonlinear Dynamics of Information Processing in Intracellular Phenomena

Tetsuya J. Kobayashi,  Tomoyuki Yamada,  Atsushi Kamimura,  

pp.33-36

Publication Date:

Online ISSN:2188-5079

DOI:10.15248/proc.1.33

PDF download (1.6MB)

Noise and stochasticity are ubiquitous within microscopic biological systems. To function stably within such noise, it has been speculated that biological systems exploit noise. However, it was recently proposed that a cell is also equipped with nonlinear dynamics, being properly designed, to effectively suppress such noise. In order to clarify the similarity and difference of the two apparently opposite possibilities, we construct a new mathematical model that can be employed for the comparison. By using the model, we analyze qualitative and quantitative properties of the noise-suppressing and noise-exploiting dynamics.

[1] M. B. Elowitz and S. Leibler. A synthetic oscillatory network of transcriptional regulators. Nature, 403(6767):335-8, January 2000.

[2] M. Ueda and T. Shibata. Stochastic signal processing and transduction in chemotactic response of eukaryotic cells. Biophysical Journal, 93:11-20, 2007.

[3] V. Shahrezaei and P.S. Swain. The stochastic nature of biochemical networks. Current Opinion in Biotechnology, 19(4):369-74, 2008.

[4] L. Gammaitoni, et al. Stochastic resonance. Reviews of Modern Physics, 70(1):223-287, 1998.

[5] D. Fraser and M. Kaern. A chance at survival: gene expression noise and phenotypic diversification strategies. Molecular microbiology, 71(6):1333-40, 2009.

[6] P. Hanngi. Stochastic Resonance in Biology. chemphyschem, 3:285-290, 2002.

[7] K. Kitajo, , et al. Behavioral Stochastic Resonance within the Human Brain. Physical Review Letters, 90(21), May 2003.

[8] R.Milo, S.Shen-Orr, S.Itzkovitz, N.Kashtan, D.Chklovskii, and U.Alon. Network motifs: simple building blocks of complex networks. Science (New York, N.Y.), 298(5594):824-7, October 2002.

[9] A. Becskei and L. Serrano. Engineering stability in gene networks by autoregulation. Nature, 405(6786):590-3, June 2000.

[10] T. J. Kobayashi. Implementation of Dynamic Bayesian Decision Making by Intracellular Kinetics. Physical Review Letters, 104(22):228104, June 2010.

[11] T. J. Kobayashi and A. Kamimura. Dynamics of intracellular information decoding. Physical Biology, 8:055007, 2011.

[12] T. J. Kobayashi. Connection between Noise-Induced Symmetry Breaking and an Information-Decoding Function for Intracellular Networks. Physical Review Letters, 106(22):228101, June 2011.

[13] C. W. Gardiner. Handbook of Stochastic Methods: for Physics, Chemistry and the Natural Sciences (Springer Series in Synergetics). Springer, 2004.

[14] W. Horsthemke and R. Lefever. Noise-Induced Transitions: Theory and Applications in Physics, Chemistry, and Biology (Springer Series in Synergetics). Springer, 2007.